Mining maximum frequent itemsets is a key problem in many data mining application.
挖掘最大频繁项目集是多种数据挖掘应用中的关键问题 。
Some characters of Data stream make that static mining method can't meet the requirements of nowadays mining application.
数据流本身的特点使得静态挖掘方法不再满足要求。
Therefore, It possesses important theoretic and practical significance to make further improvement of decision tree algorithm, make it more suitable for data mining application requirements.
因此，进一步改进决策树算法，使其更加适合数据挖掘的应用要求，具有重要的理论和现实意义。
The topic of this paper is about the research on data mining application in school union test analysis system.
本文的主题是数据挖掘在中学会考数据分析中的应用研究。
This paper introduces data mining technology, its application in medical care system, and data mining application in Gravida and Puerpera Management Information system.
介绍数据挖掘技术及其在医疗保健中的应用，以及数据挖掘在孕产妇管理信息系统中的应用。
To solve the inefficiency of data mining, application of attribute reduction algorithm in CRM data preparation is studied.
针对银行CRM中的数据冗余大、数据挖掘效率低的问题，将基于属性约简的数据预处理方法应用在银行CRM中。
To solve the inefficiency of data mining, application of attribute reduction algorithm in CRM data preparation is studied.
针对银行CRM中的数据冗余大、数据挖掘效率低的问题，将基于属性约简的数据预处理方法应用在银行CRM中。
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